I don't think this is corrected for in Figure 2: Vaccine effectiveness against coronavirus (COVID-19) hospitalisation and death involving COVID-19, by age group
If you ask me that is a considerable Healthy User Bias!?
Most interesting is perhaps jump in "vaccine effectiveness" against non-Covid mortality between 2nd and 3rd dose. Note ~20% of double-dosed did not receive 3rd dose.
At least this part was news to me: (speaking of one FOI'd source)
"Note that every death up until 21 June 2021 was recorded as unvaccinated simply because hospitals in this Trust were using the NIMS system for classifying deaths which was not up and running until then"
There is a key point you have missed about my ghost analysis. (Ghost = not in ONS sample but in NIMS). The analysis focuses on deaths in the vaccinated population. The unvaccinated denominator does not detract from the findings of this analysis.
Yes, the difference in mortality rates for the vaccinated in ONS and NIMS is not huge. The issue is that if deaths are being misclassified when there is a low percentage of mismatching to the vaccine database, then deaths which were in fact in vaccinated people end up being classified as deaths in the unvaccinated. A tiny proportion of misclassified deaths in the vaccinated can have a huge impact on the overall unvaccinated mortality because of the disproportionate sizes of those two populations.
The reason that the ghost rates matter is not because of the denominator it is because they expose the problem with the *numerator*. Analysis of all cause deaths showed the vaccinated ghosts had a very high mortality rate. https://drclarecraig.substack.com/p/deaths-among-the-ghost-population
How can the same population have one of the highest, or the highest mortality rate compared to other groups for most conditions and yet the lowest for covid? It makes no sense and certainly doesn't look like a human induced bias.
The ONS said (for 2011) they had a ~5% mismatch rate where people who were on the census did not have a record on the NIMS database that they could match to. There are all sorts of errrors, ambiguity or out of date information that could lead to this problem. If we assume a similar problem for matching death certificates to NIMS then deaths could be misclassified. The ONS said that any failure to match a death certificate to a vaccine record resulted in the assumption that the death had been in an unvaccinated person. (Note the ONS make no mention of deaths that were not matched to a NIMS record - because if they did not match they were assumed to be unvaccinated).
For a death to be classed as 'in the vaccinated' (in table 5) requires a successful match between the death certificate and a vaccine record in NIMS. For a death to be classed as unvaccinated requires no match. Therefore, any deaths in the vaccinated with different details to their NIMS entry would be misclassified as unvaccinated. Imagine a death of a vaccinated person who was in the ONS sample (in table 2). Let's say their NIMS entry used a nickname or had an error in it. The death certificate would not match to a vaccine record but it could still match to the census data. They would then be included as a death in an unvaccinated person.
Any bias this creates should be the same for the vaccinated sample in the ONS sample and those outside of it and for covid as well as all cause deaths. There must therefore be an additional issue to explain the high all cause ghost vaccinated mortality and the low covid ghost vaccinated mortality.
The big difference between covid and all cause deaths is the proportion that occur in hospital (71% vs 44%). It is fair to assume that deaths in hospital are more likely to have had their NHS record cleaned up and for those certifying to produce a certificate that is identical to the NHS record. Any cleaning up of the NHS record would automatically result in a more accurate NIMS record as they are related.
If we make very plausible assumptions that there is a difference in hospitalisation rates for the vaccinated and unvaccinated then the mortality rate anomalies can be replicated almost entirely. The assumptions are simply that
a) around 5% of death certificates do not match perfectly to the NIMS database for deaths outside of hospital
b) this falls to only 4% for deaths in hospital
c) deaths outside of hospital are slightly more likely to be vaccinated
The latter is fair given that 21% of deaths outside hospital are in care homes where it is virtually compulsory to be vaccinated.
The only difference in mortality rates between groups that this model cannot reproduce is the finding of a higher mortality rate in the vaccinated ghosts than the unvaccinated population in some groups. There must be another explanation for that.
I whole heartedly agree with your call to ask for more than just data.
Here's what I plan to ask from the ONS:
1. A reproduction of their calculations after accounting for a potential 5% error rate in matching of death certificates in the vaccinated i.e. assuming that an equivalent proportion of the unmatched were in fact vaccinated not assuming they were all unvaccinated.
2. The proportion of hospital deaths that were matched as vaccinated compared to the proportion of non-hospital deaths.
3. An estimate of the death certificate mismatch rate. For example, a sample of death certificates could be manually matched to NIMS to see the difference between more generous matching criteria and their automated matching.
Any suggestions from anyone as to other pertinent questions would be welcome.
Nice. Once again you provide an important balancing contribution to the debate. Rigorous peer review and scrutiny are what good (citizen) science demands. I'll keep reading both sides of "our side" and theirs. Thanks, Brian!
Yup. Healthy User Bias explains it. Fact is, there are far too many non-covid excess deaths two years into the vaccination program. While the ONS study compares deaths to unvaxxed, It would also be useful to compare death rate of vaxxed to the pre-COVID baseline. While this also would suffer from a HUB, a higher rate in the vaccinated compared to baseline would be a conservative indicator the vaccinated death rate is elevated.
Then of course, still to be answered is the reason “Long Covid “ or the Vax , or a synergistic combination
Given the complexity of the manufacturing process for the gene-therapy treatment for SARS-CoV-2 it seems the likelihood they didn't fuck up is low:
https://anandamide.substack.com/p/pfizer-and-moderna-bivalent-vaccines
Hey Brian, check out Figure 3 from latest ONS drop:
Figure 3: Reduction in risk of non-COVID-19 death by vaccination status shows the importance of adjusting for health-related factors
Reduction in risk of non-coronavirus (COVID-19) death by vaccination status compared with unvaccinated, England, 21 March 2021 to 20 March 2022 https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/covid19vaccineeffectivenessestimatedusingcensus2021variablesengland/31march2021to20march2022
I don't think this is corrected for in Figure 2: Vaccine effectiveness against coronavirus (COVID-19) hospitalisation and death involving COVID-19, by age group
If you ask me that is a considerable Healthy User Bias!?
Most interesting is perhaps jump in "vaccine effectiveness" against non-Covid mortality between 2nd and 3rd dose. Note ~20% of double-dosed did not receive 3rd dose.
What says ye to it?
https://wherearethenumbers.substack.com/p/claims-the-unvaccinated-were-at-higher
At least this part was news to me: (speaking of one FOI'd source)
"Note that every death up until 21 June 2021 was recorded as unvaccinated simply because hospitals in this Trust were using the NIMS system for classifying deaths which was not up and running until then"
Thank you Brian - an enjoyable read.
There is a key point you have missed about my ghost analysis. (Ghost = not in ONS sample but in NIMS). The analysis focuses on deaths in the vaccinated population. The unvaccinated denominator does not detract from the findings of this analysis.
Yes, the difference in mortality rates for the vaccinated in ONS and NIMS is not huge. The issue is that if deaths are being misclassified when there is a low percentage of mismatching to the vaccine database, then deaths which were in fact in vaccinated people end up being classified as deaths in the unvaccinated. A tiny proportion of misclassified deaths in the vaccinated can have a huge impact on the overall unvaccinated mortality because of the disproportionate sizes of those two populations.
The reason that the ghost rates matter is not because of the denominator it is because they expose the problem with the *numerator*. Analysis of all cause deaths showed the vaccinated ghosts had a very high mortality rate. https://drclarecraig.substack.com/p/deaths-among-the-ghost-population
However, the opposite was true for covid deaths. https://drclarecraig.substack.com/p/how-many-ghosts-die-with-covid
How can the same population have one of the highest, or the highest mortality rate compared to other groups for most conditions and yet the lowest for covid? It makes no sense and certainly doesn't look like a human induced bias.
The ONS said (for 2011) they had a ~5% mismatch rate where people who were on the census did not have a record on the NIMS database that they could match to. There are all sorts of errrors, ambiguity or out of date information that could lead to this problem. If we assume a similar problem for matching death certificates to NIMS then deaths could be misclassified. The ONS said that any failure to match a death certificate to a vaccine record resulted in the assumption that the death had been in an unvaccinated person. (Note the ONS make no mention of deaths that were not matched to a NIMS record - because if they did not match they were assumed to be unvaccinated).
For a death to be classed as 'in the vaccinated' (in table 5) requires a successful match between the death certificate and a vaccine record in NIMS. For a death to be classed as unvaccinated requires no match. Therefore, any deaths in the vaccinated with different details to their NIMS entry would be misclassified as unvaccinated. Imagine a death of a vaccinated person who was in the ONS sample (in table 2). Let's say their NIMS entry used a nickname or had an error in it. The death certificate would not match to a vaccine record but it could still match to the census data. They would then be included as a death in an unvaccinated person.
Any bias this creates should be the same for the vaccinated sample in the ONS sample and those outside of it and for covid as well as all cause deaths. There must therefore be an additional issue to explain the high all cause ghost vaccinated mortality and the low covid ghost vaccinated mortality.
The big difference between covid and all cause deaths is the proportion that occur in hospital (71% vs 44%). It is fair to assume that deaths in hospital are more likely to have had their NHS record cleaned up and for those certifying to produce a certificate that is identical to the NHS record. Any cleaning up of the NHS record would automatically result in a more accurate NIMS record as they are related.
If we make very plausible assumptions that there is a difference in hospitalisation rates for the vaccinated and unvaccinated then the mortality rate anomalies can be replicated almost entirely. The assumptions are simply that
a) around 5% of death certificates do not match perfectly to the NIMS database for deaths outside of hospital
b) this falls to only 4% for deaths in hospital
c) deaths outside of hospital are slightly more likely to be vaccinated
https://drclarecraig.substack.com/p/the-ons-have-a-faulty-sorting-hat
The latter is fair given that 21% of deaths outside hospital are in care homes where it is virtually compulsory to be vaccinated.
The only difference in mortality rates between groups that this model cannot reproduce is the finding of a higher mortality rate in the vaccinated ghosts than the unvaccinated population in some groups. There must be another explanation for that.
I whole heartedly agree with your call to ask for more than just data.
Here's what I plan to ask from the ONS:
1. A reproduction of their calculations after accounting for a potential 5% error rate in matching of death certificates in the vaccinated i.e. assuming that an equivalent proportion of the unmatched were in fact vaccinated not assuming they were all unvaccinated.
2. The proportion of hospital deaths that were matched as vaccinated compared to the proportion of non-hospital deaths.
3. An estimate of the death certificate mismatch rate. For example, a sample of death certificates could be manually matched to NIMS to see the difference between more generous matching criteria and their automated matching.
Any suggestions from anyone as to other pertinent questions would be welcome.
Nice. Once again you provide an important balancing contribution to the debate. Rigorous peer review and scrutiny are what good (citizen) science demands. I'll keep reading both sides of "our side" and theirs. Thanks, Brian!
Yup. Healthy User Bias explains it. Fact is, there are far too many non-covid excess deaths two years into the vaccination program. While the ONS study compares deaths to unvaxxed, It would also be useful to compare death rate of vaxxed to the pre-COVID baseline. While this also would suffer from a HUB, a higher rate in the vaccinated compared to baseline would be a conservative indicator the vaccinated death rate is elevated.
Then of course, still to be answered is the reason “Long Covid “ or the Vax , or a synergistic combination